Order Statistics And Their Use In Testing And Estimation Estimates Based On Order Statistics Of Samples From Various Populations

The CRC Handbook of Tables for the Use of Order Statistics in Estimation revises and significantly expands upon the well-known Order Statistics and Their Use in Testing and Estimation (Volume 2), published in 1970. It brings together tables relating to order statistics from many important distributions and provides maximum likelihood estimations of their parameters based on complete as well as Type-II censored samples. This practical reference describes in detail the method of computation used to construct the tables and illustrates their usefulness with practical examples. The CRC Handbook of Tables for the Use of Order Statistics in Estimation is easy to use and provides information on order statistics estimation at your fingertips.

Optimizing Method in Statistics is a compendium of papers dealing with variational methods, regression analysis, mathematical programming, optimum seeking methods, stochastic control, optimum design of experiments, optimum spacings, and order statistics. One paper reviews three optimization problems encountered in parameter estimation, namely, 1) iterative procedures for maximum likelihood estimation, based on complete or censored samples, of the parameters of various populations; 2) optimum spacings of quantiles for linear estimation; and 3) optimum choice of order statistics for linear estimation. Another paper notes the possibility of posing various adaptive filter algorithms to make the filter learn the system model while the system is operating in real time. By reducing the time necessary for process modeling, the time required to implement the acceptable system design can also be reduced One paper evaluates the parallel structure between duality relationships for the linear functional version of the generalized Neyman-Pearson problem, as well as the duality relationships of linear programming as these apply to bounded-variable linear programming problems. The compendium can prove beneficial to mathematicians, students, and professor of calculus, statistics, or advanced mathematics.

A companion volume to the authors' previous well-received work, the CRC Handbook of Tables for the Use of Order Statistics in Estimation, this handbook discusses testing whether a hypothesis is true or false. Together, these volumes are your complete reference to theory and important tables relating to order statistics and their applications. Once a researcher completes an experiment, the resulting data is assumed to have come from a normal distribution with its mean and variance unknown. The researcher is then presented with a hypothesis testing problem. The use of order statistics and related functions offers a simple, powerful, and interesting approach to solving this problem. This volume presents an introduction to the use of order statistics and explains the various problems and their applications. The role of order statistics in solving these problems is examined, several important statistics are introduced, and their use in addressing testing of hypothesis problems is highlighted. The book also includes numerous tables that facilitate the methods of hypothesis testing using order statistics. Examples are given of the use of these tables in multiple comparison tests, with attention to error rates and sample sizes, and in the analog range of analysis of variance.